Medical imaging is a well-established technique in the field of equipments for medical applications. Particularly, this technique is commonly exploited for the assessment of blood perfusion, which finds use in several diagnostic applications and especially in ultrasound analysis. For this purpose, an ultrasound contrast agent (UCA), typically in the form of a suspension of gas bubbles in a liquid carrier, is administered to a patient. The contrast agent acts as an efficient ultrasound reflector, so that it can be easily detected by applying ultrasound waves and recording a resulting echo signal. As the contrast agent flows at the same velocity as the blood in the patient, its tracking provides information about the perfusion of the blood in a body part to be analyzed.
Gas bubbles are typically stabilized using emulsifiers, oils, thickeners or sugars, or by entraining or encapsulating the gas or a precursor thereof into a variety of systems. Stabilized gas bubbles are generally referred to as “gas-filled microvesicles”. Gas-filled microvesicles include gas bubbles dispersed in an aqueous medium and bound at the gas/liquid interface by a very thin envelope involving a surfactant (i.e., an amphiphilic material). These microvesicles (also known as “microbubbles”), are prepared by contacting powdered amphiphilic materials, e.g. freeze-dried preformed liposomes or freeze-dried or spray-dried phospholipid solutions, with air or other gas and then with an aqueous carrier, and agitating to generate a microbubble suspension which is then administered shortly after its preparation.
Alternatively, the microvesicles include suspensions in which the gas bubbles are surrounded by a solid material envelope formed of natural or synthetic polymers (in this case, they are also known as “microballoons” or “microcapsules”). Another kind of ultrasound contrast agent includes suspensions of porous microparticles of polymers or other solids, which carry gas bubbles entrapped within the pores of the microparticles.
Examples of suitable aqueous suspensions of microvesicles, in particular microbubbles and microballoons, and of the preparation thereof are disclosed, for instance, in EP-A-0458745, WO-A-91/15244, EP-A-0554213, WO-A-94/09829 and WO-A-95/16467 which are incorporated by reference. An example of a commercial ultrasound contrast agent comprising gas-filled microvesicles is SonoVue® (Bracco International BV).
In a perfusion assessment process, the microvesicles are typically destroyed by an ultrasound pulse of sufficient energy (called “high mechanical index”). Observation of the replenishment rate of the microvesicles in the body-part under analysis provides information about its physiological conditions. This technique has been proposed for the first time in Wei, K., Jayaweera, A. R., Firoozan, S., Linka, A., Skyba, D. M., and Kaul, S., “Quantification of Myocardial Blood Flow With Ultrasound-Induced Destruction of Microbubbles Administered as a Constant Venous Infusion,” Circulation, vol. 97 1998 which is incorporated by reference.
For this purpose, the flow of the contrast agent is monitored by acquiring a sequence of consecutive images representing the body-part after the destruction of the microvesicles. The images are then analyzed to obtain a time-curve that represents the change in intensity of each basic area of the images. These perfusion curves are fitted to mathematical models, in order to extract quantitative parameters of the perfusion process. Examples of the above-mentioned process (also known as parametric perfusion analysis) are described, for instance, in WO-A-02/102251 and in the following publications: K. Wei, Detection and Quantification of Coronary Stenosis Severity With Myocardial Contrast Echocardiography, Progress in Cardiovascular Diseases, 44(2), 2001, 81-100; Kevin Wei, Elizabeth Le, Jian-Ping Bin, Matthew Coggins, Jerrel Thorpe, Sanjiv Kaul. Quantification of Renal Blood Flow With Contrast-Enhanced Ultrasound. J. Am Col1 Cardiol, 2001; 37:1135-40; Kharchakdjian, R., Burns, P. N., and Henkelman, M. Fractal Modeling of Microbubble Destruction-Reperfusion in Unresolved Vessels. IEEE Ultrasonics Symposium, 2001; Rim, S.-J., Leong-Poi, H., Lindner, J. R, Couture, D., Ellegala, D., Masson, H. Durieux, M, Kasse, N. F. and Kaul S., Quantification of Cerebral Perfusion with Real-Time Contrast-Enhanced Ultrasound, Circulation, vol. 104, 2001, 2582-2587; Schlosser et al, Feasibility of the Flash-Replenishment Concept in Renal Tissue: Which Parameters Affect the Assessment of the Contrast Replenishment?, Ultrasound in Med. & Biol., Vol. 27, pp 937-944, 2001; and Murthy T H, Li P, Locvicchio E, Baisch C, Dairywala I, Armstrong W F, Vannan M. Real-Time Myocardial Blood Flow Imaging in Normal Human Beings with the use of Myocardial Contrast Echocardiography. J Am Soc Echocardiogr, 2001, 14(7):698-705, which are incorporated by reference.
However, the accuracy of the perfusion assessment is adversely affected by the noise resulting from the inevitable misalignment of the images. For example, this can be due to the motion of the patient, to his/her respiratory cycle or to the involuntary movement of a measuring probe. This seriously degrades the quality of the results of the perfusion assessment. The problem is particularly acute in parametric imaging of the perfusion process; indeed, this technique requires precise alignment of the images, since any error caused by their misalignment seriously impairs the calculation of the corresponding quantitative parameters. All of the above hinders the clinical application of the above-described technique.
In order to solve this problem, the images must be re-aligned before being analyzed. For this purpose, an image of the sequence is selected as a reference; the other images (called moving images) are then re-aligned with respect to the reference image. In this way, the representation of the body-part to be analyzed remains substantially stationary.
Typically, the re-alignment is carried out manually by an operator. However, this solution is very time-consuming; moreover, the quality of the result is strongly dependent on the skill of the operator. Therefore, the manual re-alignment is not feasible in most practical applications.
Some solutions for re-aligning the images automatically have also been proposed in the last years. These solutions are based on image registration techniques, which aim at determining an optimal geometrical transformation mapping each moving image to the reference image.
For example, U.S. Pat. No. 6,490,560 which is incorporated by reference, discloses a registration method for calculating tissue perfusion using computer tomography (CT) scanners. The document discloses a method working on two-dimension images for re-aligning three-dimension volumes. In this case, each volume is represented by a sequence of (two-dimension) image slices segmenting the body-part under analysis. In the proposed method a central slice is selected in each sequence. A movement in two dimensions is determined for each central slice with respect to a reference central slice. Each volume is then corrected according to the corresponding movement. Alternatively, the same process can be repeated individually for each slice. The movement is determined by matching selected landmarks having constant shape and intensity (such as a portion of the skull). Optionally, the analysis can be restricted to a sub-region of interest so as to reduce processing time.
Moreover, U.S. Pat. No. 5,568,811, which is incorporated by reference, relates to a method of localizing tissue interfaces in ultrasound analysis. In this context, the document hints at the possibility of compensating the motion by correlating a small data cube between two different images.
However, none of the solutions known in the art is completely satisfactory. Indeed, the available registration methods provide relatively poor results in most practical situations. Particularly, the proposed solutions do not ensure an adequate level of accuracy for the parametric imaging of the perfusion process. Furthermore, the presence of speckle grains in ultrasound images can hide the information actually relating to the perfusion assessment. This may introduce errors that further decrease the quality of the process.